The DOI matches its Crossref record; 211 of the 211 references it cites were found in a registry or an index.
Lipid Nanoparticle (LNP) Enables mRNA Delivery for Cancer Therapy
Abstract
Messenger RNA (mRNA) has received great attention in the prevention and treatment of various diseases due to the success of coronavirus disease 2019 (COVID‐19) mRNA vaccines (Comirnaty and Spikevax). To meet the therapeutic purpose, it is required that mRNA must enter the target cells and express sufficient proteins. Therefore, the development of effective delivery systems is necessary and crucial. Lipid nanoparticle (LNP) represents a remarkable vehicle that has indeed accelerated mRNA applications in humans, as several mRNA‐based therapies have already been approved or are in clinical trials. In this review, the focus is on mRNA‐LNP‐mediated anticancer therapy. It summarizes the main development strategies of mRNA‐LNP formulations, discusses representative therapeutic approaches in cancer, and points out current challenges and possible future directions of this research field. It is hoped that these delivered messages can help further improve the application of mRNA‐LNP technology in cancer therapy.
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Cerami, E., Gao, J., Dogrusoz, U., Gross, B. E., Sumer, S. O., Aksoy, B. A., Jacobsen, A., Byrne, C. J., Heuer, M. L., Larsson, E., et al. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0095 · Cited by 17,455
Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine
Polack, F. P., Thomas, S. J., Kitchin, N., Absalon, J., Gurtman, A., Lockhart, S., Perez, J. L., Pérez Marc, G., Moreira, E. D., Zerbini, C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2034577 · Cited by 14,592
Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine
Baden, L. R., El Sahly, H. M., Essink, B., Kotloff, K., Frey, S., Novak, R., Diemert, D., Spector, S. A., Rouphael, N., Creech, C. B., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2035389 · Cited by 10,119
mRNA vaccines — a new era in vaccinology
Pardi, N., Hogan, M. J., Porter, F. W., & Weissman, D. (2018) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2017.243 · Cited by 4,667
PEGylation as a strategy for improving nanoparticle-based drug and gene delivery
Suk, J. S., Xu, Q., Kim, N., Hanes, J., & Ensign, L. M. (2016) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2015.09.012 · Cited by 4,523
Lipid nanoparticles for mRNA delivery
Hou, X., Zaks, T., Langer, R., & Dong, Y. (2021) · Nature Reviews Materials · doi:10.1038/s41578-021-00358-0 · Cited by 4,076
Poly(ethylene glycol) in Drug Delivery: Pros and Cons as Well as Potential Alternatives
Knop, K., Hoogenboom, R., Fischer, D., & Schubert, U. S. (2010) · Angewandte Chemie International Edition · doi:10.1002/anie.200902672 · Cited by 3,533
CRISPR-Cas systems for editing, regulating and targeting genomes
Sander, J. D., & Joung, J. K. (2014) · Nature Biotechnology · doi:10.1038/nbt.2842 · Cited by 3,153
Karikó, K., Buckstein, M., Ni, H., & Weissman, D. (2005) · Immunity · doi:10.1016/j.immuni.2005.06.008 · Cited by 2,728
Cheng, Q., Wei, T., Farbiak, L., Johnson, L. T., Dilliard, S. A., & Siegwart, D. J. (2020) · Nature Nanotechnology · doi:10.1038/s41565-020-0669-6 · Cited by 2,383
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Cited by
Isaac, I., Patel, L., Tran, N., Singam, A., Yun, D., Guha, P., Park, S., & Bhattacharya, C. (2025) · Advanced Materials · doi:10.1002/adma.202507657 · Cited by 33
Ye, L., Zhao, G., Ma, J., Gan, Q., Luo, N., Pan, D., Chen, C., Chen, X., & Ning, S. (2026) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-026-02769-3 · Cited by 10
Li, P., Dong, Z., Jiang, Q., Yu, C., Liu, Y., Yuan, R., Qiu, Y., Meng, T., Hu, F., & Yuan, H. (2026) · Journal of Controlled Release · doi:10.1016/j.jconrel.2025.114406 · Cited by 6
RNALens: Study on 5’ UTR Modeling and Cell-Specificity
Mao, L., Tian, Y., Qian, K.-W., & Song, Y. (2025) · doi:10.1101/2025.07.20.665722 · Cited by 1
Metadata
- Authors
- Zong, Y., Lin, Y., Wei, T., & Cheng, Q.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2023-11
- Volume
- 35
- Issue
- 51
- Pages
- e2303261-e2303261
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W4376868041
- Cited by
- 477
- References
- 211
- FWCI
- 35.64
- Type
- journal article
- Language
- en
- Open access
- closed
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